The New Elman ANN Application in Accuracy Improvement of Robot Navigation and Obstacle Avoidance Technology

Xiao Kun Du

doi:10.4028/www.scientific.net/AMR.383-390.1447

Paper Titles

The Optimization of ITD in Direct Air-Cooled System
p.1417

Research on the Multi-Parameters Matching Control of the Cooling System for the Diesel Engine on the Numerical Simulation Technology
p.1423

Research on Parametric Design Method of Combustion Chamber on Diesel Engine
p.1431

The Review of Technology of Power Quality Disturbances Generator
p.1441

The New Elman ANN Application in Accuracy Improvement of Robot Navigation and Obstacle Avoidance Technology
p.1447

UAV Automatic Landing Control Law
p.1452

Design and Application of Long Distance Oil & Gas Pipeline Stress & Strain Monitoring Sensor
p.1458

Modeling of Distillation Tower Temperature Based on D-FNN
p.1463

Research on a New Type of Lithium Battery String Equalization and Management System
p.1470

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 383-390The New Elman ANN Application in Accuracy...

The New Elman ANN Application in Accuracy Improvement of Robot Navigation and Obstacle Avoidance Technology

Abstract:

This paper, through the analysis of the limitation of the ultrasonic sensor in the underground drilling robot which obstacle avoidance, puts forward the solving scheme, emphasizes the compensation of temperature and humidity to ultrasonic sensor, attempts to use Elman feedback neural network approach function. Elman network hidden layer adopts Tan-sigmoid transfer function, and output layer transfer function adopts linear function, which guarantee that the network can approaches wanton function with wanton precision once it has enough layers. Proved by experiments that the measure precision of ultrasonic ranging raises two orders of grade after carrying on the temperature and humidity compensate, improves the working efficiency of obstacle avoidance in the system greatly and the ability of drilling robot’s obstacle avoidance.

You might also be interested in these eBooks

Manufacturing Science and Technology, ICMST2011

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 383-390)

Pages:

1447-1451

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.383-390.1447

Citation:

Cite this paper

Online since:

November 2011

Authors:

Xiao Kun Du

Keywords:

Elman Feedback Neural Network, Error Compensation, Obstacle Avoidance, Robot, Ultrasonic Ranging

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Doctor B. Kenewher, Doctor B. Anforof. Technological development trend and prospect of underground ore robot [J] . Australian Mining, 1994(June), 34-35.

Google Scholar

[2] Tong Feng, Xu Tian-zeng. A kind of all direction high accuracy ultrasonic ranging processing method used in guidance of moving robot, Journal of Central South University of Technology, 2000(sepc. 1): 292-295.

Google Scholar

[3] Tong Feng, Xu Xiao-mei, Xu Tian-zeng. Ultrasonic LMS adaptive delay estimate based on Inherit algorithm, Applied Acoustics, 2004(4): 292-295.

Google Scholar

[4] Si Xian-jun, Wang Zhi-liang. Moving robot multi-sensor information fusion summary[J], Electrical engineering, 2004(2), 1-5.

Google Scholar

[5] Chen Yi-lin. Feature recognition based on Elman feedback neural networks [J], Control Engineering, 2005(3), 141-143.

Google Scholar

[6] Shi Yang, Li Jun. Matlab Language Toolbox [M], Northwestern Polytechnic University Press, (1998).

Google Scholar

[7] Lou Shun-tian. Matlab 5. X program design [M]. Xi Dian University Press, (2000).

Google Scholar

[8] MBEDE J B, HUANG Xin han. Fuzzy motion planning among dynamic obstacles using artificial potential fields for robot manipulators [J]. Robotics and Autonomous Systems, 2000, 32(1): 61-72.

DOI: 10.1016/s0921-8890(00)00073-7

Google Scholar